Tracer Measurements in Growing Sea Ice Support Convective Gravity Drainage Parameterizations
Tracer Measurements in Growing Sea Ice Support Convective Gravity Drainage Parameterizations
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DOI：
10.1029/2019jc015791
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发表时间：
2020-02
期刊：
影响因子：
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通讯作者：
M. Thomas;M. Vancoppenolle;J. France;W. T. Sturges;D. Bakker;J. Kaiser;R. Glasow
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文献类型：
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作者：
M. Thomas;M. Vancoppenolle;J. France;W. T. Sturges;D. Bakker;J. Kaiser;R. Glasow
重力排水是海冰生长过程中溶质再分配的主要过程。因此，模拟重力排水是必要的，以预测海冰的物理和地球化学变量。我们评估七重力排水参数化，跨越文献中的方法的范围，在海冰生长实验中使用示踪剂测量。人造海冰在一个新的实验设施，罗兰冯诺维科夫空气-海冰室中生长到大约17厘米厚。我们使用氯化钠（最初存在于水中）和罗丹明（注入水中后，10厘米的海冰生长）作为独立的示踪剂的盐水动力学。我们测量的散装盐度的垂直剖面原位，以及散装盐度和罗丹明在实验结束时采取的离散样品。与观测结果相比，使用瑞利数诊断重力泄流的对流参数化优于简单的对流参数化和扩散参数化。这项研究是第一个数值模拟溶质解耦盐度对流重力排水参数化。我们的研究结果表明：（1）对流，瑞利数为基础的参数化是我们最准确和精确的工具，用于预测海冰散装盐度;和（2）这些参数化可以推广到盐水动力学参数化，因此可以预测任何溶质的动态生长海冰。导致海水在表面冻结，形成海冰。海水中的盐被困在新形成的海冰中，在非常咸的液体或盐水的口袋里。盐水比下面的海洋密度大得多，这导致盐水流入海洋。这个过程通常被称为重力泄油。它至关重要，影响着海洋的循环，温室气体通过海冰的运动，以及海冰藻类的营养供应。几位作者提出了模拟重力排水的方法。广义上，这些可以分为两种方法：对流和扩散。在这里，我们使用一个实验室海冰生长实验来测试这些模型。我们使用海冰中两种化学物质的测量值来跟踪盐水的运动，并将测量的浓度与模型预测的浓度进行比较。我们的研究结果表明，对流方法是我们最有力的工具，预测盐水的运动重力排水和做一个出色的工作。
Gravity drainage is the dominant process redistributing solutes in growing sea ice. Modeling gravity drainage is therefore necessary to predict physical and biogeochemical variables in sea ice. We evaluate seven gravity drainage parameterizations, spanning the range of approaches in the literature, using tracer measurements in a sea ice growth experiment. Artificial sea ice is grown to around 17 cm thickness in a new experimental facility, the Roland von Glasow air-sea-ice chamber. We use NaCl (present in the water initially) and rhodamine (injected into the water after 10 cm of sea ice growth) as independent tracers of brine dynamics. We measure vertical profiles of bulk salinity in situ, as well as bulk salinity and rhodamine in discrete samples taken at the end of the experiment. Convective parameterizations that diagnose gravity drainage using Rayleigh numbers outperform a simpler convective parameterization and diffusive parameterizations when compared to observations. This study is the first to numerically model solutes decoupled from salinity using convective gravity drainage parameterizations. Our results show that (1) convective, Rayleigh number-based parameterizations are our most accurate and precise tool for predicting sea ice bulk salinity; and (2) these parameterizations can be generalized to brine dynamics parameterizations, and hence can predict the dynamics of any solute in growing sea ice. cause sea water to freeze at the surface, forming sea ice. The salt present in the sea water is trapped in the newly formed sea ice, in pockets of very salty liquid, or brine. Brine is much denser than the ocean below, which causes the brine to drain into the ocean. This process is generally referred to as gravity drainage. It is critically important, affecting the ocean's circulation, the movement of greenhouse gases through sea ice, and the supply of nutrients to sea ice algae. Several authors have suggested ways to model gravity drainage. Broadly, these can be split into two approaches: convective and diffusive. Here, we use a laboratory sea ice growth experiment to test these models. We track the movement of brine using measurements of two chemicals in the sea ice and compare measured concentrations to those predicted by the models. Our results show that convective approaches are our most powerful tool for predicting the movement of brine by gravity drainage and do an excellent job.